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    <title>data visualization on DASYA</title>
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      <title>Framework for Systematic Performance Experiments for Machine Learning</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/pito-radt/</link>
      <pubDate>Tue, 15 Jul 2025 00:00:00 +0000</pubDate>
      
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      <description>Observing how well machine learning systems utilize hardware resources is a crucial preliminary step to improve system performance and reduce hardware waste. To do such observations, one has to collect a lot of monitoring data on hardware behavior through experiments. In our group, we have recently built a framework to aid the management of such monitoring data efficiently, called Resource-Aware Data Systems Tracker. There is a variety of work to be done on this framework to improve it.</description>
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      <title>Managing Experimental Data with DuckDB</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/pito-radtduckdb/</link>
      <pubDate>Thu, 23 Nov 2023 00:00:00 +0000</pubDate>
      
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      <description>Observing how well data-intensive systems utilize hardware resources is a crucial preliminary step to improve system performance and reduce hardware waste. To do such observations, one has to collect a lot of monitoring data on hardware behavior through experiments. In our group, we have recently built a framework to aid the management of such monitoring data efficiently, called Resource-Aware Data Systems Tracker. Currently, this framework uses Postgres data management system to keep the experimental data.</description>
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